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Real-time structured light coding for adaptive patterns

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Abstract

Coded structured light is a technique that allows the 3D reconstruction of poorly or non-textured scene areas. With the codes uniquely associated with visual primitives of the projected pattern, the correspondence problem is quickly solved by means of local information only, with robustness against disturbances like high surface curvatures, partial occlusions, out-of-field of view or out-of-focus. Real-time 3D reconstruction with one shot is possible with pseudo-random arrays, where the encoding is done in a single pattern using spatial neighbourhood. To correct more mismatched visual primitives and to get patterns globally more robust, a higher Hamming distance between all the used codewords should be suited. Recent works in the structured light field have shown a growing interest for adaptive patterns. These can account for geometrical or spectral specificities of the scene to provide better features matching and reconstructions. Up till today, such patterns cannot benefit from the robustness offered by spatial neighbourhood coding with a minimal Hamming distance constraint, because the existing algorithms for such a class of coding are designed with an offline coding only. In this article, we show that due to two new contributions, a mixed exploration/exploitation search behaviour and a O(n 2) to ∼O(n) complexity reduction using the epipolar constraint, the real-time coding of patterns having similar properties than those coded offline can be achieved. This allows to design a complete closed-loop processing pipeline for adaptive patterns.

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References

  1. Adán, A., Vázquez, A., Cerrada, C., Salamanca, S.: Moving surface extraction based on unordered hexagonal perfect submaps projection: applications to 3d feature tracking. Image Vis. Comput. 27(8), 1083–1096 (2009). doi:10.1016/j.imavis.2008.10.005

  2. Albitar, C., Graebling, P., Doignon, C.: Robust structured light coding for 3d reconstruction. In: IEEE international conference on computer vision, Rio de Janeiro, Brazil (2007)

  3. Albitar, C., Doignon, C., Graebling, P.: Calibration of vision systems based on pseudo-random patterns. In: IEEE/RSJ international conference on intelligent robots and systems, St. Louis, USA (2009)

  4. Armangué, X., Salvi, J.: Overall view regarding fundamental matrix estimation. Image Vis. Comput. 21, 205–220 (2003)

    Article  Google Scholar 

  5. Batlle, J., Mouaddib, M., Salvi, J.: (1998) Recent progress in coded structured light as a technique to solve the correspondence problem: a survey. Pattern Recognit. 31(7), 963–982 (1998)

    Article  Google Scholar 

  6. Bruijn, NGD.: A combinatorial problem. In: Nederlanske Akademie van Wetenschappen, pp 758–764 (1946)

  7. Chen, S., Li, Y., Zhang, J.: Vision processing for realtime 3d data acquisition based on coded structured light. IEEE Trans. Image Process. 17(2), 167–176 (2008)

    Article  MathSciNet  Google Scholar 

  8. Claes, K.: Structured light adapted to control a robot arm. PhD thesis, pp 33–43 (2008)

  9. Etzion, T.: Constructions for perfect maps and pseudorandom arrays. IEEE Intl. Trans. Inform. Theory 34(5/1), 1308–1316 (1988)

    Article  MathSciNet  Google Scholar 

  10. Griffin, P., Narasimhan, L., Yee, S.: (1992) Generation of uniquely encoded light patterns for range data acquisition. Pattern Recognit. 25(6), 609–616

    Article  Google Scholar 

  11. Hurlbert, G., Isaak, G.: (1993) On the de Bruijn Torus problem. J. Combin. Theory Ser. A 64, 50–62

    Article  MathSciNet  MATH  Google Scholar 

  12. Kaelbling, L.P., Littman, M.L., Moore, A.W.: Reinforcement learning: a survey. J. Artif. Intell. Res. 4, 237–285 (1996). http://www.cs.washington.edu/research/jair/abstracts/kaelbling96a.html

    Google Scholar 

  13. Kazantsev, A., Petriu, E.: Robust pseudo-random coded colored structured light technique for 3d object model recovery. In: IEEE international workshop on robotic and sensors environments, Ottawa, Canada, pp 150–155 (2008)

  14. Koninckx, T., Gool, L.V.: Real-time range acquisition by adaptive structured light. IEEE Trans. Pattern Anal. Mach. Intell. 28(3), 432–445 (2006)

    Article  Google Scholar 

  15. Lathuilière, A., Pagès, J., Salvi, J., Marzani, F.S., Voisin, Y.: An adaptive structured light pattern for the 3d profiling of colored objects. International confernce on imaging technology applications for the 21st century, pp 224–225 (2005)

  16. Li, W., Böhler, M., Schütze, R., Marzani, F.S., Voisin, Y., Boochs, F.: Use of local surface curvature estimation for adaptive vision system based on active light projection. In: Proceedings of the 10th international conference on advanced concepts for intelligent vision systems. ACIVS ’08, Springer, Berlin, pp 530–541 (2008)

  17. Mitchell, C.J.: A periodic and semi-periodic perfect maps. IEEE Trans. Inform. Theory 41(1), 88–95 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  18. Morano, A., Ozturk, C., Conn, R., Dubin, S., Zietz, S., Nissanov, J.: Structured light using pseudo-random codes. IEEE Intl. Trans. Pattern Anal. Mach. Intell. 20(3), 322–327 (1998)

    Article  Google Scholar 

  19. Morita, H., Yajima, K., Sakata, S.: (1988) Reconstruction of surfaces of 3-d objects by m-array pattern projection method. IEEE Intl. Conf. Comput. Vis. 88, 468–473 (1988)

    Google Scholar 

  20. Patterson, K.G.: (1994) Perfect maps. IEEE Intl. Trans. Inform. Theory 40(3), 743–753

    Article  MathSciNet  Google Scholar 

  21. Salvi, J., Batlle, J., Mouaddib, M.: (1998) A robust-coded pattern projection for dynamic 3d scene measurement. Pattern Recognit. Lett. 19, 1055–1065

    Article  Google Scholar 

  22. Salvi, J., Pagès, J., Batlle, J.: (2004) Pattern codifications strategies in structured light systems. Pattern Recognit. 37, 827–849

    Article  MATH  Google Scholar 

  23. Zhang, L., Curless, B., Seitz, S.M.: Rapid shape acquisition using color structured light and multi-pass dynamic programming. In: The 1st IEEE international symposium on 3d data processing, visualization, and transmission, pp 24–36 (2002)

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Acknowledgments

This work has been made possible thanks to the financial support of the Region Alsace Council.

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Authors and Affiliations

  1. LSIIT (UMR CNRS-UdS 7005), University of Strasbourg, Pôle API Boulevard Sébastien Brant, 67412, Illkirch, France

    Xavier Maurice, Pierre Graebling & Christophe Doignon

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  1. Xavier Maurice
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  2. Pierre Graebling
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  3. Christophe Doignon
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Correspondence to Xavier Maurice.

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Maurice, X., Graebling, P. & Doignon, C. Real-time structured light coding for adaptive patterns. J Real-Time Image Proc 8, 169–178 (2013). https://doi.org/10.1007/s11554-011-0200-2

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